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arXiv 2409.04786cs.DS
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击中子图的次指数参数化算法

Subexponential Parameterized Algorithms for Hitting Subgraphs

Daniel Lokshtanov, Fahad Panolan, Saket Saurabh, Jie Xue, Meirav Zehavi

AI总结:

本文提出通用框架,在具有次线性平衡分隔器的图类上将 $\mathcal{F}$-Hitting 归约为低树宽 hitting-set 实例,获得 $2^{O(k^c)}n+O(m)$ 次指数参数算法并支持加权情形。

摘要:

对于有限图集合 $\mathcal{F}$,$\mathcal{F}$-Hitting 问题旨在:给定一个来自某图类 $\mathcal{G}$、具有 $n$ 个顶点(和 $m$ 条边)的图 $G$,以及参数 $k\in\mathbb{N}$,计算 $G$ 中的一个顶点集合 $S$,使得 $|S|\leq k$,并且 $G-S$ 不包含任何与 $\mathcal{F}$ 中某图同构的子图。作为一个通用问题,$\mathcal{F}$-Hitting 涵盖了文献中被充分研究的许多基本顶点删除问题。$\mathcal{F}$-Hitting 问题具有一个简单的分支算法,运行时间为 $2^{O(k)}\cdot n^{O(1)}$;而在 ETH 假设下,它在一般图上无法在 $2^{o(k)}\cdot n^{O(1)}$ 时间内求解。本文中,我们建立了一个通用框架,用于在一大族图类上为 $\mathcal{F}$-Hitting 问题设计次指数参数化算法。具体而言,我们的框架可在任何允许平衡分隔器的图类 $\mathcal{G}$ 上,以 $2^{O(k^c)}\cdot n+O(m)$ 的运行时间求解 $\mathcal{F}$-Hitting,其中常数 $c<1$,且这些平衡分隔器的大小相对于顶点数是(强)次线性的,并相对于最大团大小是多项式的。例子包括所有多项式展开图类以及许多重要的几何交图类。我们的算法也适用于 $\mathcal{F}$-Hitting 的加权版本:在该版本中,$G$ 的每个顶点都有一个权重,目标是计算满足所需条件的最小权重集合 $S$。我们框架的核心是一个精巧的次指数分支算法,它将(上述图类上的)一个 $\mathcal{F}$-Hitting 实例归约为 $2^{O(k^c)}$ 个一般 hitting-set 实例,其中每个实例的 Gaifman 图具有 $O(k^c)$ 的树宽,常数 $c<1$ 取决于 $\mathcal{F}$ 和该图类。

英文摘要:

For a finite set $\mathcal{F}$ of graphs, the $\mathcal{F}$-Hitting problem aims to compute, for a given graph $G$ (taken from some graph class $\mathcal{G}$) of $n$ vertices (and $m$ edges) and a parameter $k\in\mathbb{N}$, a set $S$ of vertices in $G$ such that $|S|\leq k$ and $G-S$ does not contain any subgraph isomorphic to a graph in $\mathcal{F}$. As a generic problem, $\mathcal{F}$-Hitting subsumes many fundamental vertex-deletion problems that are well-studied in the literature. The $\mathcal{F}$-Hitting problem admits a simple branching algorithm with running time $2^{O(k)}\cdot n^{O(1)}$, while it cannot be solved in $2^{o(k)}\cdot n^{O(1)}$ time on general graphs assuming the ETH. In this paper, we establish a general framework to design subexponential parameterized algorithms for the $\mathcal{F}$-Hitting problem on a broad family of graph classes. Specifically, our framework yields algorithms that solve $\mathcal{F}$-Hitting with running time $2^{O(k^c)}\cdot n+O(m)$ for a constant $c<1$ on any graph class $\mathcal{G}$ that admits balanced separators whose size is (strongly) sublinear in the number of vertices and polynomial in the size of a maximum clique. Examples include all graph classes of polynomial expansion and many important classes of geometric intersection graphs. Our algorithms also apply to the \textit{weighted} version of $\mathcal{F}$-Hitting, where each vertex of $G$ has a weight and the goal is to compute the set $S$ with a minimum weight that satisfies the desired conditions. The core of our framework is an intricate subexponential branching algorithm that reduces an instance of $\mathcal{F}$-Hitting (on the aforementioned graph classes) to $2^{O(k^c)}$ general hitting-set instances, where the Gaifman graph of each instance has treewidth $O(k^c)$, for some constant $c<1$ depending on $\mathcal{F}$ and the graph class.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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